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Multidimensional Linguistic Analysis of Multiple Undergraduate Writing Samples Collected from Engineering Students in Entry-level Laboratory Courses at Three Universities

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

18

Permanent URL

https://peer.asee.org/37520

Download Count

48

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Paper Authors

biography

Dave Kim Washington State University-Vancouver

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Dr. Dave Kim is Professor and Mechanical Engineering Program Coordinator in the School of Engineering and Computer Science at Washington State University Vancouver. His teaching and research have been in the areas of engineering materials, fracture mechanics, and manufacturing processes. In particular, he has been very active in pedagogical research in the area of writing pedagogy of engineering laboratory courses. Dr. Kim and his collaborators attracted close to $1M research grants to study writing transfer of engineering undergraduates. For the technical research, he has a long-standing involvement in research concerned with manufacturing of advanced composite materials (CFRP/titanium stack, GFRP, nanocomposites, etc.) for automotive, marine, and aerospace applications. His recent research efforts have also included the fatigue behavior of manufactured products, with the focus of fatigue strength improvement of aerospace, automotive, and rail structures. He has been the author or co-author of over 200 peer-reviewed papers in these areas.

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biography

Matt Frye Oregon Institute of Technology

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Matt Frye is an Assistant Professor of Communication at Oregon Institute of Technology, where he primarily teaches technical and professional writing courses. At OIT, Matt is also the Technical Communication Curriculum Coordinator for both primary university campuses and their online campus and the chair of the university Assessment Commission's executive committee.

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Wendy Michelle Olson Washington State University-Vancouver

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Abstract

This study aims to identify the linguistic feature characteristics of multiple writing assignments completed by engineering undergraduates, including entry-level engineering laboratory reports and writing produced in non-engineering courses. We used Biber’s multidimensional analysis (MDA) method as the analysis tool for the student writing artifacts. MDA is a corpus-analysis methodology that utilizes language processing software to analyze text by parts of speech (e.g. nouns, verbs, prepositions, etc.). MDA typically identifies six “dimensions” of linguistic features that a text may perform in, and each dimension is rated along a continuum. The dimensions used in this study include Dimension 1: Informational vs involved, Dimension 3: Context dependence, Dimension 4: Overt persuasion, and Dimension 5: Abstract vs. non-abstract information. In AY 2019-2020, total of 97 student artifacts (N = 97) were collected. For this analysis, we grouped documents into similar assignment genres: research-papers (n = 45), technical reports and analyses (n = 7) and engineering laboratory reports (n = 35), with individual engineering students represented at least once in the laboratory report and once in another category. Findings showed that engineering lab reports are highly informational, minimally-persuasive, and used deferred elaboration. Students’ research papers in academic writing courses, conversely, were highly involved, highly persuasive, and featured more immediate elaboration on claims and data. The analyses above indicate that students are generally performing as expected in lab report writing in entry-level engineering lab classes, and that this performance is markedly different from their earlier academic writing courses, such as first-year-composition (FYC) and technical communication/writing, indicating that students are not merely “writing like engineers” from their first day at college. However, similarities in context dependence suggest that engineering students must still learn to modulate their languages in writing dramatically depending on the writing assignment. While some students show little growth from one context to another, others are able to change their register or other linguistic/structural features to meet the needs of their audience.

Kim, D., & Frye, M., & Olson, W. M. (2021, July), Multidimensional Linguistic Analysis of Multiple Undergraduate Writing Samples Collected from Engineering Students in Entry-level Laboratory Courses at Three Universities Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37520

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